AI Governance for People Leaders: The Guardrails That Let You Move Faster

Not based on what your vendor calls the tool, based on what it actually decides about people: who gets hired, who gets developed or flagged

Apply a three-question risk-tiering logic live to tools your team uses today

Leave with a completed AI inventory for your function, a real artifact, not a case study worksheet

Most people leaders use these terms interchangeably. They are not the same thing

Responsible AI is the standard. AI Governance is the system that enforces it, and Compliance is the evidence.

The gap between them is where legal and reputational exposure lives

Who approved it, who can override a single output, what gets logged

The document you hand your CHRO, CLO, General Counsel, or a regulator if a decision gets challenged

Completed in the session, not taken home as homework

Apply the 8-question vendor evaluation framework to a real vendor your team uses, with the answer key.

Score each answer: evidence, partial, or dodge. Map each score to a decision: accept, accept with conditions, escalate, or walk away

Leave with a completed vendor accountability assessment for one real tool, with a decision recommendation attached

The EU AI Act classifies AI in employment and education as high-risk. Article 4 makes AI literacy your obligation

NYC requires bias audits for automated hiring tools. The EEOC has already enforced against AI hiring bias.

Apply six Responsible AI principles with worked examples from both HR and L&D to set your operating standard.

A risk-tiered inventory entry, a governance map, and a vendor accountability assessment for one tool.

Together, these form the start of a real governance file, not a certificate and a folder of notes.

Built in four hours on a tool your team actually uses, from hiring platforms to LMS to coaching chatbots.